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Code Review & Quality

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fdhhhdjd
Code Review & Quality

Five-axis code review for comprehensive quality assessment

Overview

Publisherfdhhhdjd
RepositoryClass-AI-Agent
Skill nameCode Review & Quality
Stars
268
Forks
168
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by fdhhhdjd on GitHub. Read the source before you install it.

Installation

Install the Code Review & Quality AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/fdhhhdjd/Class-AI-Agent/tree/main/.claude/skills/code-review
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/fdhhhdjd/Class-AI-Agent.git /tmp/Class-AI-Agent
mkdir -p .claude/skills
cp -r /tmp/Class-AI-Agent/.claude/skills/code-review .claude/skills/fdhhhdjd-code-review-quality
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Code Review & Quality in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Code Review & Quality on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Code Review & Quality is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Code Review & Quality Skill

Philosophy

"Approve a change when it definitely improves overall code health, even if it isn't perfect."

Progress over perfection. Continuous incremental improvement.


Five-Axis Review Framework

Axis 1: Correctness

Questions to ask:

  • Does the implementation match the specification?
  • Are edge cases handled?
  • Are error paths covered?
  • Are there potential runtime issues?
    • Off-by-one errors
    • Race conditions
    • Null/undefined access
    • Resource leaks

Test adequacy:

  • Do tests verify the claimed behavior?
  • Are negative cases tested?
  • Would a bug slip through?

Axis 2: Readability & Simplicity

Questions to ask:

  • Can another engineer understand this without explanation?
  • Are names clear and descriptive?
  • Is control flow straightforward?
  • Is the code organized logically?

Complexity checks:

  • Deep nesting (> 3 levels)?
  • Long functions (> 30 lines)?
  • Clever tricks that obscure intent?
  • Unnecessary abstractions?

Axis 3: Architecture

Questions to ask:

  • Does this follow existing patterns in the codebase?
  • Are module boundaries respected?
  • Is there code duplication that should be extracted?
  • Is the abstraction level appropriate?
  • Do dependencies flow in the right direction?

Over-engineering checks:

  • Is this simpler than it needs to be?
  • Are there abstractions "for future use"?
  • Would a simpler approach work?

Axis 4: Security

Input validation:

  • Is user input validated and sanitized?
  • Are queries parameterized?
  • Is output properly encoded?

Authentication & Authorization:

  • Are auth checks in place?
  • Is ownership verified for resources?
  • Are permissions enforced?

Secrets management:

  • No hardcoded secrets?
  • Sensitive data excluded from logs?
  • External data treated as untrusted?

Axis 5: Performance

Common issues:

  • N+1 query patterns?
  • Unbounded operations (loops, queries)?
  • Missing pagination?
  • Unnecessary re-renders (React)?
  • Objects created in hot paths?
  • Missing indexes for queries?

Async handling:

  • Are async operations properly awaited?
  • Could operations be parallelized?

Change Sizing Guidelines

SizeLinesGuidance
Ideal~100Easy to review thoroughly
Acceptable~300Requires focused review
Too Large1000+Split into smaller PRs

Each PR should be one logical change, not an entire feature.


Comment Severity Labels

Use prefixes to clarify intent:

LabelMeaningAction Required
(none)Required changeMust fix before merge
Critical:Merge blockerMust fix before merge
Nit:Minor/styleOptional, author's choice
Optional:SuggestionConsider, not required
FYI:InformationalNo action needed

Examples:

Critical: This allows SQL injection via the `name` parameter.

Nit: Consider renaming `data` to `userData` for clarity.

Optional: You could use `Array.from()` here instead of spread.

FYI: We have a shared utility for this in `src/utils/format.ts`.

Review Process

Step 1: Understand Context

  • What is this PR trying to achieve?
  • Is there a linked issue or spec?
  • What's the scope of changes?

Step 2: Review Tests First

Tests reveal:

  • What behavior is expected
  • What edge cases are considered
  • Whether coverage is adequate

Step 3: Examine Implementation

Walk through changes with the 5 axes in mind.

Step 4: Categorize Findings

  • Must fix — Correctness, security, critical bugs
  • Should fix — Readability, architecture concerns
  • Consider — Suggestions, style preferences

Step 5: Provide Actionable Feedback

❌ "This is confusing"

✅ "This nested conditional is hard to follow. Consider extracting 
    the inner logic to a named function like `isEligibleForDiscount()`"

Review Output Format

markdown
## Review: [PR Title]

### Summary
[1-2 sentences on overall assessment]

### Critical Issues
- **[file:line]** [Issue description]

### Important
- **[file:line]** [Issue description]

### Suggestions
- **[file:line]** [Suggestion]

### Verdict
- [ ] Approve
- [ ] Request changes
- [ ] Needs discussion

Rules

  • Don't accept "I'll clean it up later" — It won't happen
  • Remove dead code — Don't comment it out
  • Review within 1 business day — Faster is better
  • Be kind, not nice — Honest feedback helps everyone
  • One approval minimum — Before any merge

Frequently asked questions

What does the Code Review & Quality AI skill do?

Five-axis code review for comprehensive quality assessment

Why use Code Review & Quality on TypingMind?

Because you install it once and use it with any model. Code Review & Quality is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Code Review & Quality in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/fdhhhdjd/Class-AI-Agent/tree/main/.claude/skills/code-review. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Code Review & Quality?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Code Review & Quality?

As many as you like. As long as a model supports skills, you can use Code Review & Quality with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Code Review & Quality AI skill free?

It is published on GitHub by fdhhhdjd. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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